Machine vision fire behavior prediction system

Abstract

The invention discloses a machine vision fire behavior prediction system. The system comprises a data acquisition module which is used for acquiring forest environment data and gas phase data of a corresponding region and providing data support for fire behavior prediction, a data processing module which receives the data acquired by the data acquisition module, processes the data, performs comparative analysis in combination with big data so as to predict a fire behavior, and transmits a prediction result to the central processing unit, a big database module which is used for storing forest-related parameters and fire-related standard data, storing forest fire over the years, inputting and storing expert guidance schemes, and providing judgment and learning basis for the data processing module, and an early-warning inspection module which is used for receiving the fire early-warning signal, determining a fire prediction site according to positioning of the area positioning module, determining and discharging fire hidden dangers through multi-mode inspection, and performing prevention and control on a forest in a fire area in advance when uncontrollable factors exist, so that fire spreading is avoided when a fire occurs, and fire loss is reduced.

Description

technical field [0001] The invention relates to the technical field of fire protection, in particular to a machine vision fire prediction system. Background technique [0002] Fire is one of the disasters that seriously threaten the survival and development of human beings. The occurrence of fire has the characteristics of high frequency and large span of time and space, and the loss caused is also very serious. All enterprises and departments are well aware of the dangers of fire and the importance of fire prevention and fire fighting, but they really suffer from the lack of a very perfect and timely prevention and alarm method. Fire requires 24-hour all-weather, uninterrupted monitoring and analysis without dead ends, and real-time alarm. Humans can do analysis but cannot do 24-hour uninterrupted monitoring. [0003] In recent years, forest fires have caused us even greater losses, not only in property, but also in life and species diversity. There are thousands of large...

AI Technical Summary

Problems solved by technology

It returns the ecosystem to its original state and destroys the habitat of animals, which seriously damages the basic living environment of biodiversity. It will take at least several hundred years to restore such an ecosystem, and the existing technologies are basically Only after the fire broke out can it be discovered and issued an early warning, such as smoke alarms and fire central control alarm systems. They are basically judged by the smoke and heat generated after the fire breaks out, and the timeliness is not high. Every second after the fire breaks out All are ever-changing and uncontrollable, and this kind of alarm system is lagging behind. Therefore, we propose a machine vision fire prediction system to solve the above problems

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